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Название: Cyber-Physical Systems: Data Science, Modelling and Software Optimization
Автор: Alla G. Kravets, Alexander A. Bolshakov
Издательство: Springer
Год: 2024
Страниц: 229
Язык: английский
Формат: pdf (true), epub
Размер: 37.2 MB
This book is devoted to new approaches to modeling and design of cyber-physical systems. Nowadays, cyber-physical systems become widely used in different domains. Scientific society suggests new approaches to engineering and optimization of cyber-physical systems, however, there are still open questions that need to be covered by research and development. It presents results and findings in the field of Data Science and digital twin engineering for cyber-physical systems. This book provides scientific, practical, and methodological approaches to modeling of complex processes for cyber-physical systems. The authors highlight essential results on software optimization in cyber-physical systems. The first part focuses on Data Science solutions for cyber-physical systems. It covers topics such as analyzing industrial cyber-physical systems, methods for processing and analyzing large data streams, patent array analysis using a combination of ClickHouse and HDFS, and utilizing patient medical descriptions to enhance the feature space in cyber-physical breast cancer identification systems. The second part is dedicated to modelling in cyber-physical systems. This includes examples of modelling the operation of digital twins, simulating agricultural unmanned vehicles, modelling the flexibility of administrative documents, mathematical modelling of electrolysis technology for hydrogen production, and modelling hydroelastic vibrations of channel walls. The third part deals with optimizing cyber-physical systems software. It presents a new method for automatically increasing the efficiency of vectorization, selecting stochastic parameters of parallel population algorithms and the ranging impact on the solution's quality, and genetic quantum algorithms.
Автор: Alla G. Kravets, Alexander A. Bolshakov
Издательство: Springer
Год: 2024
Страниц: 229
Язык: английский
Формат: pdf (true), epub
Размер: 37.2 MB
This book is devoted to new approaches to modeling and design of cyber-physical systems. Nowadays, cyber-physical systems become widely used in different domains. Scientific society suggests new approaches to engineering and optimization of cyber-physical systems, however, there are still open questions that need to be covered by research and development. It presents results and findings in the field of Data Science and digital twin engineering for cyber-physical systems. This book provides scientific, practical, and methodological approaches to modeling of complex processes for cyber-physical systems. The authors highlight essential results on software optimization in cyber-physical systems. The first part focuses on Data Science solutions for cyber-physical systems. It covers topics such as analyzing industrial cyber-physical systems, methods for processing and analyzing large data streams, patent array analysis using a combination of ClickHouse and HDFS, and utilizing patient medical descriptions to enhance the feature space in cyber-physical breast cancer identification systems. The second part is dedicated to modelling in cyber-physical systems. This includes examples of modelling the operation of digital twins, simulating agricultural unmanned vehicles, modelling the flexibility of administrative documents, mathematical modelling of electrolysis technology for hydrogen production, and modelling hydroelastic vibrations of channel walls. The third part deals with optimizing cyber-physical systems software. It presents a new method for automatically increasing the efficiency of vectorization, selecting stochastic parameters of parallel population algorithms and the ranging impact on the solution's quality, and genetic quantum algorithms.